By: Steven Whitaker
Re-posted from: https://blog.glcs.io/variables-and-functions
Variables and functions
are the building blocks
of any programmer’s code.
Variables allow computations to be reused,
and functions help keep code organized.
In this post,
we will cover some of the basics
of variables and functions
in Julia,
a relatively new,
free, and open-source programming language.
In particular,
we will discuss what a variable is,
what sorts of data
can be assigned to a variable,
and
how to define and use functions.
Variables
A variable is a label
used to refer to an object.
julia> a = 1
1
In the above code snippet,
we assigned a value of 1
to a variable called a.
Now we can use a in other expressions,
and the value of a (1 in this case)
will be used.
julia> a + 2
3
We can also reassign variables.
julia> a = 4
4
julia> a = "Hello"
"Hello"
julia> a = [1, 2, 3]
3-element Vector{Int64}:
1
2
3
We can even use Unicode characters!
We can write many math symbols
by typing the corresponding LaTeX command
and then pressing <tab>.
Here,
we assign
(a Julia constant equal to \( \pi \)
and typed with \pi<tab>)
to
(typed with \theta<tab>).
julia> =
= 3.1415926535897...
Variables Are Labels
One important thing to remember about variables
is that they are labels for data,
not the data itself.
Let’s illustrate what that means.
At this point,
a refers to a Vector.
We will create another variable, b,
and assign it the value of a.
julia> b = a
3-element Vector{Int64}:
1
2
3
Now let’s change one of the elements of b.
julia> b[1] = 100; b
3-element Vector{Int64}:
100
2
3
We didn’t change a,
so it should be the same as before, right?
Nope!
julia> a
3-element Vector{Int64}:
100
2
3
What happened?
Remember, a is just a label
for some data (a Vector).
When we created b,
we created a new label
for the same data.
Both a and b refer
to the same data,
so modifying one modifies the other.
If you want b
to have the same values as a
but refer to different data,
use copy.
julia> b = copy(a)
3-element Vector{Int64}:
100
2
3
julia> b[1] = 1; b
3-element Vector{Int64}:
1
2
3
julia> a
3-element Vector{Int64}:
100
2
3
Now that we know
how to create variables,
let’s learn about
some basic types of data
we can assign to variables.
Basic Types
Julia has many basic data types.
integer = 9000
floating_point = 3.14
boolean = true
imaginary = 1 + 2im
rational = 4//3
char = 'x'
str = "a string"
array = [1.0, 2.0]
Integers and floating-point numbers
can be expressed
with different numbers of bits.
Int64, Int32, Int16 # and more
Float64, Float32, Float16 # and more
By default,
integer numbers
(technically, literals)
are of type Int64 on 64-bit computers
or of type Int32 on 32-bit computers.
(Note that Int is shorthand for Int64 or Int32
for 64-bit or 32-bit computers, respectively.
Therefore, all integer literals are of type Int.)
On the other hand,
floating-point numbers (literals)
of the form 3.14 or 2.3e5
are of type Float64 on all computers,
while those of the form 2.3f5
are of type Float32.
To use different numbers of bits,
just use the appropriate constructor.
julia> Int16(20)
20
julia> Float16(1.2)
Float16(1.2)
Basic Operations
Now we will cover
some basic operations.
This is by no means an exhaustive list;
check out the Julia documentation
for more details.
# Math
addition = 1 + 2.0
subtraction = 1 - 1
multiplication = 3 * 4//3
division = 6 / 4
integer_division = 6 4 # Type \div<tab>
power = 2^7
# Boolean
not = !false
and = true && not
or = not || and
# Comparison
equality = addition == 1
greater = division > integer_division
chained = addition < subtraction <= power
# Strings
string_concatenation = "hi " * "there"
string_interpolation = "1 - 1 = $subtraction"
string_indexing = string_interpolation[5]
substring = string_concatenation[4:end]
parsing = parse(Int, string_indexing)
# Arrays
a = [1, 2, 3]
b = [4, 5, 6]
concat_vert = [a; b]
concat_horiz = [a b]
vector_indexing = b[2]
vector_range_indexing = b[1:2]
matrix_indexing = concat_horiz[2:3,1]
elementwise1 = a .+ 1
elementwise2 = a .- b
# Displaying
print(addition)
println(string_concatenation)
@show not
@info "some variables" power a
Function Basics
Some of the basic operations we saw above,
e.g., parse and print,
were functions.
As demonstrated above,
functions are called
using the following familiar syntax:
func() # For no inputs
func(arg1) # For one input
func(arg1, arg2) # For two inputs
# etc.
Note that just writing the function name
(i.e., without parentheses)
is valid syntax, but it is not a function call.
In this case,
the function name is treated essentially like a variable,
meaning, for example, it can be used as an input
to another function.
For example,
one way to compute the sum
of the absolute value
of an array of numbers
is as follows:
julia> sum(abs, [-1, 0, 1])
2
Here,
the function abs is not being called (by us)
but is used as an input to the function sum
as if it were a variable.
Function Vectorization
Often,
we have a function
that operates on a single input
that we want to apply
to every element of an array.
Julia provides a convenient syntax
to do so:
just add a dot (.).
For example,
the following takes the absolute value
of every array element:
julia> abs.([-1, 0, 1])
3-element Vector{Int64}
1
0
1
There is also a function, map,
that does the same thing
in this example:
julia> map(abs, [-1, 0, 1])
3-element Vector{Int64}
1
0
1
(Note, however,
that map and the dot syntax
are not always interchangeable.)
Defining Functions
When writing Julia code,
it is convenient
to place code inside of functions.
There are two main syntaxes
for creating a function.
- Using the
functionkeyword:function myfunc(x) return x + 1 end - Using the assignment form:
myfunc2(x, y) = x + y
Optional Arguments
Sometimes we want a function
to have optional inputs.
The syntax for specifying optional arguments is
function myfunc3(required, optional = "hello")
println(required, optional)
end
Here,
optional is optional
and has a default value of "hello"
if not provided by the caller.
julia> myfunc3("say ")
say hello
julia> myfunc3("see you ", "later")
see you later
Keyword Arguments
Another way to specify optional arguments
is to use keyword arguments.
The syntax is almost the same
as regular optional arguments,
except we use a semicolon (;) instead of a comma (,).
function myfunc4(x; y = 3)
return x * y
end
Here,
y is optional,
but to specify it
we need to use the keyword y.
julia> myfunc4(2)
6
julia> myfunc4(2; y = 10)
20
julia> myfunc4(2, 10)
ERROR: MethodError: no method matching myfunc4(::Int64, ::Int64)
When calling myfunc4
we can also use a comma
when specifying y.
julia> myfunc4(2, y = 1)
2
Returning Multiple Values
Sometimes we need a function
to return multiple values.
The way to do this in Julia
is to return a Tuple.
Here’s an example:
function plusminus1(x)
return (x + 1, x - 1)
end
Then multiple variables can be assigned at once.
julia> (plus1, minus1) = plusminus1(1)
(2, 0)
julia> plus1
2
julia> minus1
0
Note that taking the output
of a function with multiple return values
and assigning it to a single variable
will assign that variable the whole Tuple of outputs.
The following code illustrates this
and shows how to return just one output:
julia> both = plusminus1(1);
julia> both
(2, 0)
julia> (one,) = plusminus1(1);
julia> one
2
(Note, however, that in this last case
the second output is still computed;
it is just immediately discarded,
so there are no savings in computation.)
Vectorizing a Function with Multiple Return Values
Vectorizing a function with multiple return values
requires a bit more work.
For this example,
we will use the sincos function
that computes the sine and cosine simultaneously.
We can still use the dot syntax,
but we might be tempted to try the following:
julia> (s, c) = sincos.([0, /2, ]);
julia> s
(0.0, 1.0)
julia> c
(1.0, 6.123233995736766e-17)
Here, s has the value of sincos(0),
not the value of sin.([0, /2, ])
like we might have expected.
Instead, we can do the following:
julia> sc = sincos.([0, /2, ])
3-element Vector{Tuple{Float64, Float64}}:
(0.0, 1.0)
(1.0, 6.123233995736766e-17)
(1.2246467991473532e-16, -1.0)
julia> s = first.(sc)
3-element Vector{Float64}:
0.0
1.0
1.2246467991473532e-16
julia> c = last.(sc)
3-element Vector{Float64}:
1.0
6.123233995736766e-17
-1.0
(Note that instead of using first or last,
we could write it this way:
output_i = getindex.(sc, i).
This way also works for functions
that return more than two values.)
Summary
In this post,
we learned about what a variable is
and some basic data types.
We also learned about
how to define and use functions.
There is a lot more we could cover
about these topics,
so if you want to learn more,
check out the links below,
or write a comment below
letting us know what additional concepts or topics
you would like to see!
Understand variables and functions in Julia?
Move on to the
next post to learn how to master the Julia REPL!
Or,
feel free to take a look
at our other Julia tutorial posts!